README.txt  
Replication Data for: Bureaucratic Responsiveness in Humanitarian Aid: Media Attention and Diversity as a Determinant of US Complex Emergency Aid
Author: Kelsey Oliver Imanishi
Email: k-oliver@osipp.osaka-u.ac.jp  
Journal: Foreign Policy Analysis

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1. OVERVIEW  
This dataset contains replication materials for the article titled "Bureaucratic Responsiveness in Humanitarian Aid: Media Attention and Diversity as a Determinant of US Complex Emergency Aid". The dataset includes all the variables used in the analysis, as well as the scripts/code necessary to reproduce the tables and figures presented in the article.

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2. FILES INCLUDED  

- `readme.txt` — This file  
- `script_main data_fpa.R`- A file containing the code used to produce the data in the main document
- `script_appendix_fpa.R` - A file containing the code used to produce statistical and regression data found in Appendix A
- `script_topic model_fpa.R` - A file containing the code used to produce LDA topic model results found in Appendix A and Appendix B
- markdown_main data_fpa.Rmd - An R markdown file that serves as a log file for the main data script
- `markdown_appendix_fpa.Rmd` - An R markdown file that serves as a log file for the appendix script
- `markdown_topic model_fpa.Rmd` - An R markdown file that serves as a log file for the topic model script
- `maindata_fpa_replication.csv` - A file containing the main data set
- `raw_articles.csv` - A file containing the original New York Times news articles used in the analysis
- `LDAtopicmodel_k250.rds` - A file containing the saved R output for the LDA topic model
- `perplexity_results.rds` - A file containing the saved R output for the perplexity results
- `tm_col_DTM.rds` - A file containing the saved R output for the document term matrix 
- `tunes_topicnumbers.rds` - A file containing the saved R output for the ldatuning of the topic model

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3. SOFTWARE REQUIREMENTS  

This analysis was conducted using R version 4.1.0. You will need the following packages: 

ape  
broom  
dplyr  
doParallel  
fixest  
ggplot2  
ggcorrplot  
gridExtra  
interactions  
ldatuning  
margins  
mice  
miceadds  
purrr  
quanteda  
quanteda.textstats  
scales  
stargazer  
stringr  
textmineR  
tidytext  
tidyr  
tidyverse  
topicmodels  
wesanderson 

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4. VARIABLE OVERVIEW  

Key variables in the dataset include:  
- `case - a country or region that contains an OFDA-declared emergency of the nature "complex emergency" or "complex food security emergency"
- year - the fiscal year
- adj_ofda - the amount of OFDA aid allocated in constant 2019 dollars
- affected_ofda - the number of individuals affected by an emergency as assessed by OFDA
- lag_trade_bal - a one-year lag of trade balance in constant 2019 dollars
- lag_adj_gdp - a one-year lag of GDP per capita in constant 2019 dollars
- lag_pop - a one-year lag of a country's population
- troops - the number of US troops present within a case country
- ch_words - the number of words discussing a case country within congressional hearing documents
- med_words - the number of words of New York Times coverage in articles focused on a given case country after data processing
- med_h - the normalized entropy value for media coverage of a given case country; used to indicate media diversity
- org_med_words - the number of words of New York Times coverage on a given case country before data processing
- log [xxx] - the natural log of any of the aforementioned variables

Please see the main document for more detailed discussion of variables and source materials. 
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5. NOTES ON REPLICATION  

- The scripts are designed to run from a root directory. You may need to adjust file paths to match your local setup.  
- All results in the paper can be reproduced using the scripts provided.    

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6. CITATION  

If you use or build on this data, please cite the original article as:  
Imanishi, KO (2025). "Bureaucratic Responsiveness in Humanitarian Aid: Media Attention and Diversity as a Determinant of US Complex Emergency Aid." Foreign Policy Analysis, Vol(xx), pp-pp.  

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7. CONTACT  

For questions about this data or analysis, please contact:  
Kelsey Oliver Imanishi  
Osaka School of International Public Policy
The University of Osaka 
Email: k-oliver@osipp.osaka-u.ac.jp

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